def test_explain(gpu):
c = Context()
data_frame = dd.from_pandas(pd.DataFrame({"a": [1, 2, 3]}), npartitions=1)
c.create_table("df", data_frame, gpu=gpu)
sql_string = c.explain("SELECT * FROM df")
assert sql_string.startswith(
"DaskTableScan(table=[[root, df]]): rowcount = 100.0, cumulative cost = {100.0 rows, 101.0 cpu, 0.0 io}, id = "
)
c.create_table("df", data_frame, statistics=Statistics(row_count=1337), gpu=gpu)
sql_string = c.explain("SELECT * FROM df")
assert sql_string.startswith(
"DaskTableScan(table=[[root, df]]): rowcount = 1337.0, cumulative cost = {1337.0 rows, 1338.0 cpu, 0.0 io}, id = "
)
c = Context()
data_frame = dd.from_pandas(pd.DataFrame({"a": [1, 2, 3]}), npartitions=1)
sql_string = c.explain(
"SELECT * FROM other_df", dataframes={"other_df": data_frame}, gpu=gpu
)
assert sql_string.startswith(
"DaskTableScan(table=[[root, other_df]]): rowcount = 100.0, cumulative cost = {100.0 rows, 101.0 cpu, 0.0 io}, id = "
)
def test_explain():
c = Context()
data_frame = dd.from_pandas(pd.DataFrame({"a": [1, 2, 3]}), npartitions=1)
c.create_table("df", data_frame)
sql_string = c.explain("SELECT * FROM df")
assert (
sql_string
== f"LogicalProject(a=[$0]){os.linesep} LogicalTableScan(table=[[schema, df]]){os.linesep}"
)
